Examining Deep Learning Models with Multiple Data Sources for COVID-19 Forecasting

27 October 2020

Papers citing "Examining Deep Learning Models with Multiple Data Sources for COVID-19 Forecasting"

6 / 6 papers shown

Title
Data-Centric Epidemic Forecasting: A Survey Alexander Rodríguez Harshavardhan Kamarthi Pulak Agarwal Javen Ho Mira Patel Suchet Sapre B. Prakash OOD 31 18 0 19 Jul 2022
Multiwave COVID-19 Prediction from Social Awareness using Web Search and Mobility Data Jia Xue T. Yabe Kota Tsubouchi J. Ma S. Ukkusuri 21 8 0 22 Oct 2021
Epidemic Dynamics via Wavelet Theory and Machine Learning, with Applications to Covid-19 To Tat Dat Protin Frédéric Nguyen T.T. Hang Martel Jules N. Thang ... Rodríguez Willy Figueroa Susely H. Lê W. Tuschmann N. Zung 13 16 0 27 Oct 2020
Short-term forecasting COVID-19 cumulative confirmed cases: Perspectives for Brazil M. Ribeiro Ramon Gomes da Silva V. Mariani L. Coelho 54 421 0 21 Jul 2020
Modelling transmission and control of the COVID-19 pandemic in Australia S. Chang Nathan Harding C. Zachreson Oliver M. Cliff M. Prokopenko 49 550 0 23 Mar 2020
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,138 0 06 Jun 2015